FIG. 1 illustrates a supply chain 100. A set of manufacturers, 102_1 and 102_2, distribute products to a set of warehouses 104_1 and 104_2, respectively. Warehouse 104_1 then distributes products to first and second distributors 106_1 and 106_2, while warehouse 104_2 distributes products to third and fourth distributors 106_3 and 106_4. The first distributor 106_1 then distributes products to one or more retail outlets, such as a first retailer 108_1. The remaining distributors distribute products to retails 108_2, 108_3, and 108_4.
Arrows 110 illustrate the insertion of counterfeit goods into the supply chain 100. In one case, counterfeit goods are introduced at a warehouse 104_2 and in another case counterfeit goods are introduced at a distributor 106_4. In either case, enterprises downstream from the counterfeit insertion event have a difficult time identifying the counterfeit goods.
Arrow 112 illustrates a possible path for an improper resale or return of an item. In this case, the distributor 106_2 is bypassed and therefore the resale and return rules potentially enforced by the distributor 106_2 are bypassed.
Arrows 114 illustrate potential improper import paths into the supply chain 100. In this case, distributor 106_1 and retailer 108_1 directly receive improperly imported goods. Thus, import restrictions to be enforced by warehouses 104 are bypassed.
The foregoing supply chain abuses and many other supply chain abuses are coming under increasing scrutiny. In addition, there is growing interest in tracking product movement to optimize legitimate supply chain operations. For example, improved information on the movement of a product through a supply chain allows enterprises to more closely analyze trends in product consumption. This allows enterprises to implement the supply chain more efficiently. In addition, more comprehensive supply chain information allows more accurate predictions of future consumption patterns.
The potential to thwart supply chain abuses and to improve supply chain efficiency has led various government agencies and large commercial enterprises to require the use of radio frequency (RG) tags. A radio frequency tag is analogous to a bar code in the sense that it is used to uniquely identify a product. However, where a bar code relies upon a visual pattern to uniquely identify a product, an RF tag uses an RF signal signature to uniquely identify a product. An RF tag reader or scanner adjacent to an RF tag records the presence of the RF tag. The reader or scanner can then deliver RF tag information to a database, allowing the RF tag information to be processed.
While the use of RF tags within a single enterprise (e.g., a manufacturer, a warehouse, a distributor, or a retailer) is known, there are many challenges associated with the use of RF tags across enterprises (e.g., tracking RF tag information from a manufacturer through a retailer). One problem with cross-enterprise analysis is efficient processing of the vast amount of information associated with the movement of multiple products through multiple tiers of multiple supply chains.
In view of the foregoing, it would be highly desirable to provide a technique for the efficient processing of cross-enterprise RF tag information. Ideally, the processing of this information is used to improve the function of the supply chain and to identify abuses within the supply chain.